# Contributing to the AI Dictionary of Terms

Thank you for your interest in contributing to the AI Dictionary of Terms! This project is a living, breathing resource, and it grows stronger with every contribution. Whether you're fixing a typo, updating an outdated definition, or adding a brand-new term, your help is deeply appreciated.

## 🚀 How to Add a New Term

1. **Fork the Repository**: Click the "Fork" button at the top right of this page to create your own copy of the dictionary.
2. **Create a New File**: 
   - Navigate to the `/terms/` directory.
   - Click **Add file** > **Create new file**.
   - Name the file using `kebab-case` (e.g., `neuro-symbolic-ai.md`).
3. **Use the Template**: 
   - Copy the contents of the [Term Template](templates/term-template.md).
   - Paste it into your new file.
4. **Fill Out the Sections**: 
   - Ensure every section is completed. 
   - **Crucial:** The "Simple Version" must be written in plain, jargon-free English. This is the core philosophy of this dictionary.
5. **Update the README**: 
   - Add your new term to the appropriate category in the `## 📂 Browse by Category` section.
   - Add your new term to the `##  Browse All Terms (A-Z)` table in the correct alphabetical order.
   - Update the total term count in the `## Quick Stats` section.
6. **Submit a Pull Request (PR)**: 
   - Commit your changes and open a Pull Request to the `main` branch of this repository.
   - Add a brief description of the term you added.

## ✏️ How to Improve Existing Terms

Found a typo? Is a definition outdated? Is the "Simple Version" still too technical? 
1. Navigate to the term's `.md` file in the `/terms/` directory.
2. Click the **pencil icon** (Edit) in the top right.
3. Make your edits and write a clear commit message (e.g., `docs: simplify explanation for LLM`).
4. Submit a Pull Request.

## 📝 Style Guidelines

To maintain consistency across the dictionary, please adhere to the following rules:
- **Tone**: Professional, accessible, and encouraging. 
- **The "Simple Version"**: Must be understandable by a non-technical person (e.g., a high school student or a colleague in HR). Use analogies!
- **Business Context**: Must focus on real-world enterprise applications, ROI, or operational impact.
- **Code Examples**: Must be clean, well-commented, and use standard libraries (like PyTorch, Hugging Face, or scikit-learn).
- **No Plagiarism**: Write definitions in your own words. You can link to external sources for further reading.

## 🤝 Code of Conduct

Please be respectful and constructive in all interactions. We are building this resource to promote AI literacy for everyone. Harassment, spam, or promotional content will not be tolerated.

Thank you for helping make AI accessible to everyone!